Trust, control strategies and allocation of function in human-machine systems

TLDR

As automated controllers replace human intervention, operators shift from active control to supervisory roles, and improper allocation between automatic and manual control can degrade system performance, with trust influencing the decision to use manual or automatic modes. The study experimentally examines how operators' trust evolves during interaction with a semi‑automatic pasteurization plant and how this relates to their control strategy choices. The authors use regression analysis to identify factors driving trust changes and develop a trust‑transfer function via LIME series analysis to model trust dynamics. The analysis yields a model that predicts the choice between manual and automatic control from operators' trust in automation and their self‑confidence in manual control.

Abstract

As automated controllers supplant human intervention in controlling complex systems, the operators' role often changes from that of an active controller to that of a supervisory controller. Acting as supervisors, operators can choose between automatic and manual control. Improperly allocating function between automatic and manual control can have negative consequences for the performance of a system. Previous research suggests that the decision to perform the job manually or automatically depends, in part, upon the trust the operators invest in the automatic controllers. This paper reports an experiment to characterize the changes in operators' trust during an interaction with a semi-automatic pasteurization plant, and investigates the relationship between changes in operators' control strategies and trust. A regression model identifies the causes of changes in trust, and a 'trust transfer function' is developed using lime series analysis to describe the dynamics of trust. Based on a detailed analysis of operators' strategies in response to system faults we suggest a model for the choice between manual and automatic control, based on trust in automatic controllers and self-confidence in the ability to control the system manually.